GitLab

* Add a custom training loop for NCF model with TF2.0

* Fix long line in ncf_keras_main.py

* Remove dataset repeat when using custom training loop.

this is not going to help with current tf.data semantics. so removing it.

* Fixes that make transformer run.

* Remove debug print statements.

* Changed the permissions to 644.

* Fix the rest of the permissions.

* enable static batch in all benchmarks

* Restrict dist strat hack to training mode

For now we will do predict/eval without dist strat, so remove that hack in non training cases.

* Use `inputs` instead of `x` as arg name for call

Keras has different behavior based on whether the inputs are called `inputs` or not. Using `inputs` gives expected behaviors.

* Avoid extra map fn on input in dist strat case

* Update how we handle custom metrics

This new approach works with and without dist strat. The previous one didn't work with dist strat. We need to fix that but this is reasonable in meantime (b/133724664).

* Update benchmarks

* typo in metrics code

* Revert metrics change

Didn't actually work in distributed case..

250347237  by A. Unique TensorFlower<gardener@tensorflow.org>:

    Fix linting errors in BERT benchmark test.

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250326131  by A. Unique TensorFlower<gardener@tensorflow.org>:

    Internal change

250315593  by A. Unique TensorFlower<gardener@tensorflow.org>:

    Internal change

250303528  by haoyuzhang<haoyuzhang@google.com>:

    Add method docstring to fix lint error.

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PiperOrigin-RevId: 250347237

* Run different numbers of steps on different platforms

* Add new tests for delayed performance measurement

This shuffling should help in getting shuffling each epoch.

250009207  by A. Unique TensorFlower<gardener@tensorflow.org>:

    Add feature in BERT to write training metrics to a summary file.

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PiperOrigin-RevId: 250009207

249896208  by hongkuny<hongkuny@google.com>:

    Adds __init__.py

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PiperOrigin-RevId: 249896208

Add early stopping logic to ncf keras when desired threshold is met. Also change the default batch size to match the tuned hyperparams

249883771  by hongkuny<hongkuny@google.com>:

    Creates a benchmark dir

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PiperOrigin-RevId: 249883771

* Moved common keras code to utils.

* Initial 1 gpu benchmark

- Aligned flags with resnet example
- removed code/features that are not super useful
- eval as part of train if bleu source/ref provided
- add exp_per_second hook

* Rename benchmark classes, pass batch-size and log_steps.

* fix docstring

* Predict done with checkpoints inline

- perfzero baseclass

* steps not epochs with smoother training loop.

* do not initialize history outside loop.

* 5000 between eval not 500

* estimator to keras.

* remove epochs var.

* use range not xrange.

* 200K steps for 1 gpu

* fix global step

* Add a graph optional_next Reset benchmark.

* Fix lint error.

* Merged commit includes the following changes:
249776315  by tianlin<tianlin@google.com>:

    Internal change

249763206  by tianlin<tianlin@google.com>:

    For TF 2.0 (related to Beam Search), expand cond dims in tf.where(cond, x, y) to make all parameters broadcastable.

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249392724  by hongkuny<hongkuny@google.com>:

    Internal change

PiperOrigin-RevId: 249776315

* Merged commit includes the following changes:
249823043  by tianlin<tianlin@google.com>:

    Bring back v2 test for predict and eval.

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PiperOrigin-RevId: 249823043

* Add a test enabling get_next_as_optional behavior.

* Remove repeated flag.

* Remove trailing space.

* Make the name shorter.

* Fix lint error.

* Refine the benchmark name.

Adding validation every epoch allows us to view the progress during training instead of having to wait until the last eval. Mostly useful for manual runs.

Current batch size 160000 does not converge to the desired HR. So we decrease to 99k which is known to converge. Tested locally and got to 63.5 at epoch 7. Also decreasing number of epochs as I don't see any improvement after epoch 7-8.

249580533  by A. Unique TensorFlower<gardener@tensorflow.org>:

    Internal change

249566870  by A. Unique TensorFlower<gardener@tensorflow.org>:

    Set up BERT benchmark test.

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PiperOrigin-RevId: 249580533

* Add enable_get_next_as_optional flag.

* Set enable_get_next_as_optional to strategy.

* Add comments to explain the flag.

* Remove trailing whitespace.

* Remove trailing space.

249500988  by hongkuny<hongkuny@google.com>:

    Lints

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PiperOrigin-RevId: 249500988

* Add big tests.

* fix super

* Add fp16, increase 8xGPU batch-sizes

* Adding the rest of the fp16 tests.

* Big accuracy test batch_perf_gpu

* fix docstrings

* add _run_and_report

* Edited docstrings

* Merged commit includes the following changes:
249218656  by tianlin<tianlin@google.com>:

    Deal with imports, fix a typo and make unit tests fast.

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249198645  by tianlin<tianlin@google.com>:

    Trivial: Remove one empty line before "import tensorflow"

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249195490  by tianlin<tianlin@google.com>:

    Initialize Transformer TF V2 Model with Keras subclassing implementation. (Compatible with TF V1)

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249195008  by tianlin<tianlin@google.com>:

    Internal change

249173564  by hongkuny<hongkuny@google.com>:

    Internal change

249079258  by hongkuny<hongkuny@google.com>:

    Internal change

247691534  by haoyuzhang<haoyuzhang@google.com>:

    Internal change

247533725  by haoyuzhang<haoyuzhang@google.com>:

    Internal change

247509295  by haoyuzhang<haoyuzhang@google.com>:

    Internal change

247311355  by wangtz<wangtz@google.com>:

    Internal change

247303127  by wangtz<wangtz@google.com>:

  ...

249377254  by hongkuny<hongkuny@google.com>:

    Internal change

249373328  by hongkuny<hongkuny@google.com>:

    Clean up tf import

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249333938  by hongkuny<hongkuny@google.com>:

    Fix tf1 import

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249325089  by hongkuny<hongkuny@google.com>:

    BERT 2.0

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249173564  by hongkuny<hongkuny@google.com>:

    Internal change

PiperOrigin-RevId: 249377254

* Delete accuracy if exists in eval results.

* get global_step only if it exists in eval results

This will allow one to easily reproduce a benchmark by running with the flags.

* Set the --clone_model_in_keras_dist_strat to None.  Remove the separate no_cloning benchmarks and add a couple of cloning ones.  Fixes the learning rate schedule to cache its ops per graph.

* Added 'tfdata_exp' version of all benchmarks which set
FLAGS.tf_data_experimental_slack = True. Renamed
`data_prefetch_with_slack` to `data_delay_prefetch` (haoyu's change)
to make the names more distinct.

* Add flag to resnet input pipeline and surface through
keras_imagenet_main.py

- Test passes locally python3 and test is already
    skipped for python2.

* Add FP16 and benchmarks.

* add missing run and report.

* Add loss_scale as option not included with dtype.

* move loss_scale validation under dtype conditional.

* add loss_scale to flags tested.

* Fix trivial model to work properly with fp16

* Add comment on manual casting

Previously we had one dense layer in trivial model. The weight was [224*224*3, num_classes].
Using two dense layers, the weights are [224*224*3, 1] and [1, num_classes].

* Do not report metrics in performance benchmarks

* Rename flag